Loyola University Maryland

Data Science

Micro-Credential Program

The online Data Science or Analytics micro-credential prepares professionals to be leaders in the field of data science. Enrolled students experience insights and training to incorporate dynamic emerging data science opportunities into their work. By implementing the knowledge, strategies, and techniques learned, students are better positioned to take their career to the next level. 

Data Science Analytics
CS703 - Programming for Data Science CS701 - Introduction to Programming
DS730 - Introduction to Data Science
ST710 - Statistical Computing

Both the Data Science and Analytics micro-credential are suitable for professionals of all levels. From individual practitioners engaged in promoting data science, to those working in major private, non-profit, and governmental data science-related organizations, students learn not only the skills to take advantage of the latest trends and platforms in data science, but how to apply them.

Both programs are ideal for prospective students who work in the data science industry, or those who seek to enter a field that is full of opportunity. Those who complete the Data Science or Analytics micro-credential program will have studied the latest trends in data science leave prepared to take their organization into the future. Designed from the ground up to be flexible, the micro-credential is entirely online, which translates to a life, work, education balance.

Students may complete either the Data Science or Analytics micro-credential in as little as 1 years.

Applicants who meet the entrance standards of the program for which they are applying are admitted as nondegree students.

It is the student's responsibility to make certain that the minimum QPA requirement of 3.000, which is a B average, is maintained. The receipt of one grade of C+ (2.330) or lower in the first two courses will result in dismissal from the program. The receipt of one F (0.000) will result in dismissal from the program. A student has the right to appeal an academic dismissal.

Individuals who wish to continue beyond the micro-credential program must formally apply for admission to the Master of Science in Data Science program through the standard application process. Students may not continue to enroll beyond the three credits until they have been admitted into the Master of Science in Data Science program. To avoid program interruption, students should apply after their third course, otherwise there may be a break or semester lost in the continuity of the program. The application fee is waived, and the application process is streamlined and accelerated for current Loyola nondegree students.

To apply, you must:

  • Submit a completed application form
  • Official transcripts from all degree-granting institutions attended 
  • Pay the non-refundable $60 application fee.
  • Please note the following application deadlines: 
    • The deadline to submit a Fall application as a Nondegree Student is August 1. 
    • The deadline to submit a Spring application as a Nondegree Student is December 1.

* Please note: nondegree students are not eligible for federal financial aid.

The application will be reviewed to assess the student’s background in computer programming and statistics. At a minimum, students are expected to have taken a college-level introductory statistics course. Additionally, only those with prior experience in computer programming may start in the Data Science micro-credential. Applicants to the micro-credential program must select "Non-degree, Data Science" as the Degree of Interest in the application.

Admission and How to Apply

For questions or inquiries regarding the program please request information below, email graduate@loyola.edu, or call 410-617-5020. Students interested in applying to this program are encouraged to begin the application early to ensure all materials and transcripts are received on time. More information about admission requirements may be on the admission page.

Request Information

Paul Tallon

Paul Tallon, Ph.D.

As a professor of information systems, Dr. Tallon yearns for his students to engage in the burgeoning world of technology

Information Technology and Operations Management